Data Science for Sensory and Consumer Scientists [First Edition] 9780367862879, 1130063375, 9781032384962, 9781003028611

Table of contents :
1.
Bienvenue!.........................................................................................................................1
1.1 WhyDataScienceforSensoryandConsumerScience?..................1
1.1.1 CorePrinciplesinSensoryandConsumerScience.............1
1.1.2 ComputationalSensoryScience...............................................7
2.
Getting
Started.............................................................................................................9
2.1 IntroductiontoR.......................................................................................9
2.1.1 WhatIsR?....................................................................................9
2.1.2 WhyLearnR(orAnyProgrammingLanguage)?..............9
2.1.3 WhyR?........................................................................................10
2.1.4 WhyRStudio/Posit?................................................................11
2.1.5 InstallingRandRStudio.........................................................12
2.2 GettingStartedwithR..........................................................................12
2.2.1 Conventions.................................................................................12
2.2.2 InstallandLoadPackages.......................................................13
2.2.3 FirstAnalysisinR....................................................................15
2.2.4 RScripts......................................................................................16
2.2.5 CreateaLocalProject.............................................................17
2.3 FurtherTipsonHowtoReadThisBook?.......................................18
2.3.1 Introduction to {magrittr} and the Notion of Pipes.....19
2.3.2 Tibbles..........................................................................................21
2.3.3 CallingVariables........................................................................26
2.3.4 Printingvs. SavingResults.....................................................27
2.3.5 RunningCodeandHandlingErrors.....................................29
2.4 VersionControl/GitandGitHub........................................................30
2.4.1 Git..................................................................................................30
2.4.2 GitHub..........................................................................................31
3.
Why
Data
Science?..................................................................................................33
3.1 HistoryandDefinition............................................................................33
3.2 BenefitsofDataScience.........................................................................35
3.2.1 ReproducibleResearch.............................................................35
3.2.2 StandardizedReporting...........................................................35
3.3 DataScientificWorkflow........................................................................36
3.3.1 DataCollection..........................................................................36
3.3.2 DataPreparation.......................................................................37
vii
viii Contents
3.3.3 DataAnalysis.............................................................................38
3.3.4 ValueDelivery............................................................................40
3.4 HowtoLearnDataScience...................................................................41
3.5 Cautions:Don’tDoThatEverybodyDoes......................................41
4.
Data
Manipulation...................................................................................................43
4.1 WhyManipulatingData?......................................................................43
4.2 TidyingData.............................................................................................45
4.2.1 SimpleManipulations...............................................................45
4.2.2 ReshapingData..........................................................................59
4.2.3 TransformationThatAlterstheData.................................63
4.2.4 CombiningDatafromDifferentSources.............................67
5.
Data
Visualization....................................................................................................73
5.1 Introduction...............................................................................................73
5.2 DesignPrinciples......................................................................................74
5.3 TableMaking............................................................................................76
5.3.1 Introduction to {flextable}...................................................76
5.3.2 Introdution to {gt}...................................................................80
5.4 ChartMaking............................................................................................85
5.4.1 Philosophy of {ggplot2}.........................................................85
5.4.2 Getting Started with {ggplot2}...........................................85
5.4.3 CommonCharts.........................................................................97
5.4.4 Miscealleneous..........................................................................100
5.4.5 Few Additional Tips and Tricks..........................................107
6.
Automated
Reporting.........................................................................................113
6.1 WhatandWhyAutomatedReporting?..........................................113
6.2 IntegratingReportswithinAnalysisScripts..................................114
6.2.1 Excel............................................................................................115
6.2.2 PowerPoint................................................................................120
6.2.3 Word ...........................................................................................130
6.2.4 NotesonApplyingCorporateBranding ...........................132
6.3 Integrating Analyses Scripts Within Your Reporting Tool........133
6.3.1 What Is {rmarkdown}............................................................133
6.3.2 Starting with {rmarkdown}...................................................134
6.3.3 {rmarkdown} through a Simple Example.........................134
6.3.4 Creating a Document Using {knitr}................................136
6.3.5 Example of Applications........................................................136
6.4 ToGoFurther......................................................................................137
Contents ix
7.
Example
Project:
The
Biscuit
Study.......................................................139
7.1 ObjectiveoftheTest ............................................................................139
7.2 Products...................................................................................................140
7.3 SensoryDescriptiveAnalysis..............................................................140
7.4 Consumer Test........................................................................................141
7.4.1 Participants...............................................................................141
7.4.2 Test Design................................................................................141
7.4.3 Evaluation..................................................................................143
8.
Data
Collection.........................................................................................................145
8.1 DesignsofSensoryExperiments........................................................145
8.1.1 General Approach....................................................................145
8.1.2 Crossover Designs....................................................................147
8.1.3 BalancedIncompleteBlockDesigns(BIBD)...................150
8.1.4 IncompleteDesignsandSensoryInformedDesignsfor
Hedonic Tests............................................................................151
8.2 Product-related Designs.......................................................................155
8.2.1 Factorial Designs......................................................................155
8.2.2 Mixture Designs.......................................................................155
8.2.3 ScreeningDesigns....................................................................159
8.2.4 SensoryInformedDesignsforProductDevelopment....160
8.3 Execute.....................................................................................................161
8.4 Import.......................................................................................................164
8.4.1 ImportingStructuredExcelFile.........................................165
8.4.2 ImportingUnstructuredExcelFile ....................................166
8.4.3 Importing Data Stored in Multiple Sheets.......................168
9.
Data
Preparation....................................................................................................171
9.1 Introduction.............................................................................................171
9.2 Inspect.......................................................................................................172
9.2.1 Data Inspection........................................................................172
9.2.2 Missing Data.............................................................................175
9.2.3 DesignInspection....................................................................185
9.3 Clean.........................................................................................................188
9.3.1 Handling Data Type...............................................................188
9.3.2 Converting between Types....................................................196
10.
Data
Analysis.............................................................................................................199
10.1 Sensory Data...........................................................................................199
10.2 Demographic and Questionnaire Data.............................................207
10.2.1 DemographicData:FrequencyandProportion..............207
10.2.2 EatingBehaviorTraits:TFEQData.................................211
10.3 Consumer Data.......................................................................................217
x Contents
10.4 Combining Sensory and Consumer Data.........................................222
10.4.1 Internal Preference Mapping................................................222
10.4.2 ConsumersClustering ............................................................225
10.4.3 Drivers of Liking......................................................................230
10.4.4 External Preference Mapping...............................................235
11.
Value
Delivery...........................................................................................................239
11.1 HowtoCommunicate?.........................................................................239
11.2 Exploratory, Explanatory, and Predictive Analysis......................241
11.3 Audience Awareness..............................................................................242
11.3.1 TechnicalAudience.................................................................244
11.3.2 Management..............................................................................244
11.3.3 GeneralInterest.......................................................................244
11.4 MethodstoCommunicate...................................................................249
11.4.1 ConsidertheMechanism .......................................................249
11.4.2 Pick the Correct Format........................................................250
11.5 Storytelling..............................................................................................251
11.5.1 TheBeginning(Context)......................................................252
11.5.2 The Middle (Action and Impact)........................................253
11.5.3 The End (Conclusion)............................................................253
11.6 Reformulate.............................................................................................254
12.
Machine
Learning...................................................................................................255
12.1 Introduction.............................................................................................255
12.2 Introduction of the Data......................................................................257
12.3 Machine Learning Methods.................................................................257
12.4 Unsupervised Machine Learning........................................................258
12.4.1 DimensionalityReduction.....................................................259
12.4.2 Clustering..................................................................................261
12.5 Supervised Learning..............................................................................264
12.5.1 Workflow....................................................................................265
12.5.2 Regression..................................................................................265
12.5.3 OtherCommonSupervisedMLAlgorithms....................267
12.6 Practical Guide to Supervised Machine Learning.........................268
12.6.1 Introduction to the {tidymodels} Framework...............268
12.6.2 SamplingtheData..................................................................269
12.6.3 Cross-Validation.......................................................................269
12.6.4 Data Preprocessing {recipes}............................................270
12.6.5 ModelDefinition......................................................................271
12.6.6 SettheWholeProcessintoaWorkflow............................271
12.6.7 Tuning the Parameters...........................................................272
12.6.8 Model Training.........................................................................272
12.6.9 ModelEvaluation....................................................................273
Contents xi
13.
Text
Analysis..............................................................................................................279
13.1 Introduction to Natural Language Processing...............................279
13.2 Application of Text Analysis in Sensory and
Consumer Science..................................................................................280
13.2.1 Text Analysis as Way to Describe Products....................280
13.2.2 Objectives of Text Analysis..................................................281
13.2.3 ClassicalTextAnalysisWorkflow.......................................282
13.2.4 Warnings....................................................................................282
13.3 Illustration Involving Sorting Task Data.........................................283
13.3.1 DataPreprocessing.................................................................283
13.3.2 Introduction to Working with Strings ({stringr}).......284
13.3.3 Tokenization..............................................................................284
13.3.4 SimpleTransformations.........................................................285
13.3.5 SplittingFurthertheTokens................................................286
13.3.6 Stopwords..................................................................................287
13.3.7 Stemming and Lemmatization.............................................289
13.4 TextAnalysis..........................................................................................292
13.4.1 RawFrequenciesandVisualization....................................293
13.4.2 Bigramsandn-grams .............................................................298
13.4.3 Word Embedding.....................................................................299
13.4.4 Sentiment Analysis..................................................................300
13.5 ToGoFurther......................................................................................300
14.
Dashboards...................................................................................................................301
14.1 Objectives ................................................................................................301
14.2 Introduction to Shiny through an Example....................................302
14.2.1 What Is a Shiny Application?..............................................302
14.2.2 Starting with Shiny.................................................................302
14.2.3 Illustration.................................................................................302
14.2.4 DeployingtheApplication....................................................308
14.3 ToGoFurther......................................................................................308
14.3.1 PersonalizingandTuningYourApplication....................309
14.3.2 Upgrading Tables.....................................................................309
14.3.3 BuildingDashboard................................................................310
14.3.4 Interactive Graphics................................................................311
14.3.5 InteractiveDocuments...........................................................311
14.3.6 Documentation and Books....................................................312
15.
Conclusion
and
Next
Steps.............................................................................313
15.1 Other Recommended Resources.........................................................313
15.2 Useful R Packages..................................................................................314
Bibliography..............................................................................................................................317
Index ............................................................................................................................................327

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